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Adaptive Collaborative Detection for Opportunistic Vehicle Sensor Networks
Author(s) -
Yuanyuan Zeng
Publication year - 2014
Publication title -
international journal of distributed sensor networks
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.324
H-Index - 53
eISSN - 1550-1477
pISSN - 1550-1329
DOI - 10.1155/2014/275609
Subject(s) - computer science , testbed , participatory sensing , event (particle physics) , scheme (mathematics) , cluster analysis , wireless sensor network , real time computing , computer network , artificial intelligence , data science , mathematical analysis , physics , mathematics , quantum mechanics
Transportation is a huge problem that curbs development of societies and economy in many countries nowadays. Participatory sensing technologies encourage people to be involved in environment monitoring through smart devices. Vehicle sensor networks (VSNs) are a novel solution for road event detection with advantages. In this paper, we consider runtime road event detection using VSNs to satisfy the application-specific requirements through collaboration among vehicles. A group road detection scheme (GRD) by using dynamic clustering in VSNs is presented to improve detection performance with low time complexity and message complexity. The simulations with testbed of 5 remote controllable vehicles show that GRD scheme provides effectiveness under different road scenarios.

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